The present invention relates generally to motion capture, and more particularly to methods and systems for cleaning and stabilizing facial motion marker data.
Motion capture systems are used to capture the movement of a real object and map it onto a computer-generated object as a way of animating it. These systems are often used in the production of motion pictures and video games for creating a digital representation of an object or person that is used as source data to create a computer graphics (“CG”) animation. In a typical system, an actor wears a suit having markers attached at various locations (e.g., small reflective markers are attached to the body and limbs). Precisely-placed digital cameras then record the actor's body movements in a capture space from different angles while the markers are illuminated. The system later analyzes the images to determine the locations (e.g., spatial coordinates) and orientations of the markers on the actor's suit in each frame. By tracking the locations of the markers, the system creates a spatial representation of the markers over time and builds a digital representation of the actor in motion. The motion is then applied to a digital model in virtual space, which may then be textured and rendered to produce a complete CG representation of the actor and/or the performance. This technique has been used by special effects companies to produce realistic animations in many popular movies.
Capturing the motion manifesting an actor's facial expressions entails an approach similar to capturing body movements. However, it is not practical for the actor to wear a “suit” on his or her face. Moreover, human facial expressions involve facial muscle movements significantly more subtle than typical body motions. For facial motion capture, relatively small-sized markers are affixed directly to the actor's face, positioned to define facial movement, and applied in sufficient number to capture the many subtle types of facial muscle movements. However, a large number of markers and their proximities makes post-capture frame-to-frame marker tracking difficult, and requires significant manual processing to ensure that each individual marker is accurately tracked.